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November 9, 2021

Hire Now, Stay Forever: The Benefits of Predictive Analytics and Career Mapping

Employee turnover has been a hot topic for many years, as companies struggle to keep their best talent in-house. With a tighter hiring market due to the pandemic, organizations are redoubling their efforts to keep their best people engaged for the long term. 

Helping an employee plan their career can seem daunting, full of unpredictable variables and a host of unknowns. Use of AI, including predictive analytics, can help employees and their mentors map careers that keep them within the company while also unleashing their full potential.

How “Career Path” Became “Career Turnover” 

The question “Why do workers leave their employers?” has long been a discussion point, as companies work to retain top talent.

For many employers, the answer to this question is close at hand. At least 75 percent of the reasons people voluntarily leave their jobs are related to the local work environment. In other words, they are factors that managers and employers can influence, says Jim Harter, Gallup’s chief scientist for workplace management and wellbeing. 

Opportunities to acquire new skills may lead employees to leave, especially if those opportunities are not offered within the organization. A Prudential survey, for example, found that while 95 percent of respondents didn’t think their jobs would be replaced by technology, 30 percent also felt they didn’t have the skills they needed to do their job today, and 50 percent said they wouldn’t have the necessary skills in a decade, writes Kristi Broom, VP, product operations at upskilling platform Degreed. 

Skill building and career growth are among the biggest drivers of employee turnover. The Work Institute’s 2020 Retention Report, for example, found that career development was the No. 1 reason workers switched employers. Career development ranked No. 1 for the 10th year in a row as to why workers quit, suggesting that employers are struggling to find ways to build meaningful career paths for their employees. 

“Employees leave because they want to learn, grow, and be challenged in their roles at work. If not challenged, they will find a job where they will be,” writes William Mahan at Work Institute.

With the demand for career growth and development so high among professionals, it is perhaps not surprising that the top organizations in nearly every industry are those that manage to encourage in-house career growth. The best companies “champion a ‘learning spirit’ within their teams, providing them plenty of opportunities to learn, stretch, and grow,” writes executive coach Marcel Schwantes.  

Leaders who provide a defined career track to their team members, along with the learning and growth opportunities necessary to build the skills for each step on that track, build a high-performing culture in the long term, he explains. 

Couple planning airplane trip to Morocco, point on map, taking notes in blank notebook; Predictive analytics concept

Using AI to Plan a Career Future

The strength of AI lies in its ability to analyze vast data sets. AI can glean meaningful insights from quantities of data too large for the human mind to parse effectively. By using AI in different ways, organizations can gain various insights and even take a peek into the future through the use of predictive analytics.

“Predictive analytics is a subcategory of data analytics focused on analyzing historical data using statistical modeling, machine learning, and data mining. Companies use information gleaned from the research to make future predictions,” writes Sakshi Gupta at Springboard. 

To better understand insights gleaned from AI and map those insights to particular employees’ career tracks, you need a clear view of the company’s structure and defined roles, writes Liz Strikwerda at WorkforceHub. Yet don’t let these structures and roles limit the ways in which employees can think about their paths. 

In the past, career mapping often limited itself to laying out the company’s structure and then plotting a course through it. Today, however, AI can help employees imagine different paths by focusing on skill analysis and development.

For example, a conventional career path for an employee may be to become a manager, then step into executive leadership as their experience grows and their perspective changes. By analyzing the skills the worker uses today, on the other hand, AI can recommend adjacent skills the worker may find easier to develop, as well as positions that demand those skills even if those positions aren’t on the conventional career ladder. 

Employees who enjoy their work because of the skills they deploy to meet its challenges may find themselves particularly well-served by predictive analytics, because the tool can recommend a career path that continues to develop those skills on new challenges without demanding a conventional leadership path. For those interested in leadership, predictive analytics can help them see which skills are essential for leaders and how to develop those skills with the opportunities available now. 

man traveler holding map; Predictive analytics concept

How to Build Your Team’s Futures In-House

Building a career is one challenge. Mapping a career so that it follows the opportunities within a particular company is another. 

Yet offering meaningful career mapping to employees can be an effective way to reduce turnover. In a study published in Management Science Letters, researchers Muhammad Shahid Nawaz and Faizuniah Pangil found that employees who received regular career guidance were less likely to consider leaving their organization for opportunities elsewhere. 

Today, the traditional upward path through an organization is only one of many options, and it isn’t necessarily the best option for every employee. Career mapping and predictive analytics help your employees think, plan, and imagine more broadly when it comes to their own professional futures. 

“Career growth can, of course, include getting a promotion and becoming a manager or team lead. But it can also mean moving into a role that better suits your goals, taking on a project where you can showcase your knowledge, and receiving positive feedback from your managers,” says Kevin Wu, founder and CEO at online tech mentorship program Pathrise. Predictive analytics can help employees imagine more opportunities to take these steps, leading to skill growth, better engagement, and a reduced desire to look outside the organization for career advancement. 

One reason for strong in-house career mapping may outweigh employee engagement when it comes to turnover: The right career mapping can also ensure the right people land in management and leadership positions. 

Why does this matter? In its “State of the American Workplace” study analyzing decades of data and interviews with 25 million employees, Gallup found that the No. 1 reason people leave their employers is poor fit with their managers. 

“The single biggest decision you make in your job–bigger than all the rest–is who you name manager. When you name the wrong person manager, nothing fixes that bad decision. Not compensation, not benefits, nothing,” writes Gallup CEO Jim Clifton. In short, people leave managers, not companies. Solid career mapping helps companies put the right people in management, further reducing turnover. 

Whether they’re aiming for management or want a different challenge, employees who receive support with career mapping are more likely to stay with their employer, says Melissa Jezior, president and CEO at Eagle Hill Consulting. Career counseling and mentorship build a supportive environment that helps employees focus on their work and their career plans, quelling the need to look elsewhere for professional fulfillment. 

Creating an in-house team to last for years or decades can be challenging. Choosing the right digital tools, like predictive analytics, can help. A clearer view of available information and past successes, based on a deep understanding of employee skill sets, can help companies ensure they put the right people on the right paths. 

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